TECHNIQUES FOR EVALUATING OPERATOR LOADING IN MAN-MACHINE SYSTEMS. MODIFICATION AND FURTHER EVALUATION OF A DIGITAL MAN-MACHINE SIMULATION MODEL

Abstract

A digital computer simulation model was previously derived and employed for simulating the performance of the operator(s) in a man-machine system. The technique is based on an analysis of the performance of each operator, arranged into ordered, discrete actions called 'subtasks,' and the compilation for each of certain source data. These data, together with selected parameter values (e.g., the time allotted for task performance), are placed in punched card form and introduced into a digital computer which sequentially simulates, according to the rules of the model, the 'performance' of each subtask by each operator. The normal sequence of subtasks may be modified if actions have to be skipped or repeated due to failure of a subtask by either operator or as a result of operator decisions. A simulation is completed when the operators either use all allotted time or successfully complete the task. Results are recorded indicating the areas of operator overload, failure, idle time, peak stress, etc., for the given set of selected parameters. Repetitions of the simulation, with different parameter values, yield a range of records.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1963
Accession Number
AD0414428

Entities

People

  • Arthur I. Siegel
  • J. Jay Wolf

Tags

Communities of Interest

  • Air Platforms
  • Ground and Sea Platforms
  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Agreements
  • Computer Programming
  • Computer Programs
  • Computers
  • Data Processing
  • Digital Computers
  • Human-Machine Systems
  • Iterations
  • Mathematical Analysis
  • Military Research
  • Normal Distribution
  • Probability
  • Random Variables
  • Standards
  • Stochastic Processes
  • Switches
  • Task Performance And Analysis

Readers

  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience
  • Computational Modeling and Simulation
  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.